The invention described herein may be manufactured and used by or for the Government of the United States of America for governmental purposes without the payment of any royalties thereon or therefor.
(1) Field of the Invention
This invention is generally related to methods and apparatus for performing medical diagnoses and particularly to a method and apparatus for enabling the diagnosis of sleep breathing disorders or other physiological respiratory dysfunction while the patient is awake.
(2) Description of the Prior Art
Sleep breathing disorders and other physiological respiratory dysfunctions in humans constitute an area requiring diagnosis. One such area is called obstructive sleep apnea or sleep disorder breathing. Within the pediatric, infant and newborn population the incidence of apparent life threatening events, sudden infant death syndrome and sleep disorder breathing have all been well documented. Sleep apnea also affects over 25% of apparently healthy adults age 55 and older. Sleep apnea contributes to daytime fatigue, increased work place accidents and a number of cardiovascular disorders. The need for a relatively easily implemented procedure exists to provide efficient methods and procedures for diagnosing these various physiological respiratory dysfunctions.
U.S. Pat. No. 4,982,738 to Griebel discloses a diagnostic apnea monitor system that records snoring and respiration sounds made by a patient as well as the patient""s heart rate while the patient is sleeping. Signals indicative of snoring sounds and the time intervals therebetween are produced from the recorded respiration. The system generates a first respiration disturbance index representing the number of intervals per hour between episodes of snoring. An average heart rate is also generated in response to the patient""s recorded second respiration disturbance index representing the number of episodes per hour in which the patient""s heart rate remained at 90% to 109% of its average rate is calculated. A physician then evaluates the first and second disturbance indices to determine whether obstructive sleep apnea is indicated.
U.S. Pat. No. 5,101,831 to Koyama et al. discloses a system for discriminating a sleep state and selectively waking a patient. This system provides variation indices representing the variation of a biological signal on the basis of a first variation amount denoting a tendency of a time series of measured biological signal to increment from the starting time of the measurement and a second variation amount denoting the temporal variation of the biological signal. These signals enable the discrimination of different sleep states, namely the NREM and REM sleep states, on the basis of the distribution of the density of the variation indices exceeding a predetermined threshold.
U.S. Pat. No. 5,105,354 to Nishimura provides a method and apparatus for correlating respiration and heartbeat variability and particularly a method for forecasting sudden infant death syndrome by investigating the correlation between respiration and heart beat in a normal state and a sleep-apnea state of a newborn. In essence the system detects respiratory information, produces an envelope indicative of the respiration information and samples the envelope to produce a fast Fourier transform spectrum of the envelope information. Simultaneously the system detects cardio-electric information in the form of an EKG, detects the peak value and calculates a sequential Rxe2x80x94R interval series that is fast Fourier transformed into a spectrum of the Rxe2x80x94R interval variation. These two complex conjugations are multiplied and, through a fast Fourier transform, analyzed to calculate a correlation between respiration and heart beat that can then be evaluated to identify the state just before the normal state of a newborn will convert to the state of sleep apnea and forecast sudden death syndrome.
U.S. Pat. No. 5,385,144 to Yamanishi et al. discloses a respiration diagnosis apparatus that distinguishes between obstructive sleep apnea and central apnea automatically. An analog signal processor generates pulse wave signals based on light received from a light emitting means and passing through or reflecting off living tissue. A pulse wave line analog signal processor extracts change components of a base line of the generated pulse wave signal. A master microcomputer distinguishes between obstructive apnea and central apnea on the basis of the extracted pulse wave base line change components.
U.S. Pat. No. 5,398,682 to Lynn discloses a method and apparatus for the diagnosis of sleep apnea utilizing a single interface with a human body part. More specifically, the diagnosis identifies the desaturation and resaturation events in oxygen saturation of a patient""s blood. The slope of the events is determined and compared against various information to determine sleep apnea.
It has also been recognized that cardio and respiratory signals are signals of non-linear dynamical systems. U.S. Pat. No. 5,404,298 to Wang et al. and U.S. Pat. No. 5,453,940 to Broomhead et al. disclose dynamical system analyzers or chaos analyzers useful in determining characteristics based upon such dynamical system signals. Additional information on the use of chaos is contained in Strogatz, Steven H., Non-linear Dynamics in Chaos, Reading, Mass., Addison Wesley Publishing Company, 1994, p. 379.
U.S. Pat. No. 5,769,084 filed by the same inventors as this application, discloses an apparatus and method for identifying the timing of the onset of and duration of an event characteristic of sleep-breathing disorder during a conventional overnight sleep study. Chaotic processing techniques analyze data concerning one or more cardio-respiratory functions, such as nasal airflow, chest wall effort, oxygen saturation, heart beat and heart activity. Excursions of the resulting signal beyond a threshold provide markers for the timing of such an event that is useful in the diagnosis of obstructed sleep apnea and other respiratory dysfunctions.
Conventional sleep studies require significant resources. Generally they are conducted in special facilities. One patient is located in one room for the night and typically arrives about 8:00 PM and leaves about 6:00 am. At least two trained technicians generally are present for the duration of each test. They attach the various sensors to the head, chest, arms and legs and then monitor the various signals from different patients. The results as multichannel charts and observed events are then reviewed by one or two physicians of different specialties in order to determine the existence of sleep apnea or other respiratory dysfunction conditions. Given this requirement, conventional sleep studies require significant physical plant assets that are not available for other purposes. In addition, the diagnosis is labor intensive.
Katz et al., xe2x80x9cA Practical Non-Linear Method for Detection of Respiratory and Cardiac Dysfunction in Human Subjectsxe2x80x9d, SPIE Vol. 2612, Page 189 (1995) hypothesizes the possibility of making a diagnosis while a patient is awake. The paper presents no quantitative results and merely plots a temporal signal dependent on a physiological function. What is needed is a diagnostic test that can screen patients sleeping disorders or other respiratory dysfunctions while the patient is awake thereby to eliminate the requirement for conventional sleep studies in many patients. Notwithstanding the existence of the foregoing prior art, the current conventional approach for diagnosing sleep apnea continues to be the diagnosis of choice.
Therefore it is an object of this invention to provide a method and apparatus for facilitating the diagnosis of sleep breathing disorders while a patient is awake.
Another object of this invention is to provide a method and apparatus for generating markers that identify the onset and duration of an event characteristic of a sleep breathing disorder while a patient is awake.
In accordance with this invention, a cardio-respiratory function is monitored over time while a patient is awake. A digitized time series representation of each monitored cardio-respiratory function is generated. Chaotic processing of the corresponding time series representation yields a processed signal. Excursions of this signal beyond a corresponding threshold value indicate the time of an onset of an event and its duration.